Autonomous Vehicles to Enter AI-powered Mobility Network

The advancement of self-driving cars aims to reduce fatal human errors on the road and ease traffic congestions.

As the auto industry embraces a paradigm shift to electric vehicles, tech giants and startup newcomers join the fray to disrupt the incumbent automakers by innovating autonomous vehicles.

The latest auto manufacturer to unveil a prototype at 2017’s South by Southwest tech conference in Austin, Texas is Nio. The Chinese-funded company, which produces Formula E racing cars, plans to sell a self-driving electric vehicle in the U.S. market in three years.

Nio enters the autonomous vehicle competition with other players such as Tesla, Google, Baidu, and Faraday Future, along with car-sharing companies Uber and Lyft team up with legacy car manufacturers like Ford and General Motors adding to the mix. Public road tests are underway in Nevada, California, Beijing and more around the world.

The development of self-driving cars began as early as in the 1980s with Carnegie Mellon University researchers assembled one with computers and sensors that aimed to avoid collisions. The project made headlines in 1995 when the car steered itself from Washington to San Diego.

Tech and electric vehicle companies had been testing and developing autonomous vehicles over the last couple of decades with the ultimate goal of producing self-driving cars for the mass market. Progress had accelerated at the turn of the decade, particularly with the success of Tesla in a number of key automotive markets globally. Today even luxury automotive design brands such as Pininfarina are bringing their world-famous sophistication to the hybrid market, showcasing glitzy models like the H600, which was developed in tandem with Chinese startup, Hybrid Kinetic.

Tesla’s fortunes were boosted by financial support provided by a number of governments – ranging from an unprecedented USD465 million loan by the U.S. Department of Energy in 2010 to a waiver of a costly first vehicle registration tax by the Hong Kong government. Government support is only expected to increase as clean energy, mitigating pollution and climate change become increasingly important.

An automated guided vehicle can change lanes, adjust its speed, and park itself without the help of a human driver. Leveraging advanced mapping systems with sensors feeding the road conditions to the computers to process driving decisions, the benefit of autonomous vehicles is to minimize traffic accidents caused by human errors.

Ideally, a more predictable traffic flow will also ease traffic congestions when all vehicles are connected to a network. This ecosystem of a mobility network is fed by data from cars on the road and the transportation infrastructure from traffic lights, bridges, and tunnels. By applying artificial intelligence to manage the mobility network, human beings will enjoy a more efficient commuting experience.

In a world where vehicles on the road can communicate with one another, venture investor Kai-Fu Lee, who bets heavily on AI, said in a recent public speech, the technology could detect cars that are about to break down, say a flat tire and alert the surrounding cars to move away, avoiding an accident.

Mr. Lee also said the network could commercially incentivize and prioritize the traffic if one vehicle is in a rush to reach its destination by paying more for other vehicles to give way.

At the same time, we can summon autonomous car at our doors at any time when the cars are not in used.

With every technological revolution progresses, the downside of it is the dissolution of certain jobs and its related business. In the case of future mobility, drivers and toll booth agents will be obsolete, and the scope of enterprises that thrive on drivers’ accountability such as auto insurance will diminish. The technology also has a way to go when it comes to safety and a sizable number of developers are working to make sure that any risks are exposed and mitigated as early as possible.

As more vehicles powered by electricity as a source of renewable energy and requiring complex computing systems, the demand for scientists and engineers in the energy, autopilot, and artificial intelligence field is on the rise.